Journal of Textile Research ›› 2021, Vol. 42 ›› Issue (05): 162-167.doi: 10.13475/j.fzxb.20200801906

• Apparel Engineering • Previous Articles     Next Articles

Evaluation modelling for maturity in intelligent manufacturing for multi-type clothing factories

DU Jinsong1,2(), YU Yayun1, ZHAO Ni1, XIE Ziang1, FEI Zhonghua3, PAN Jingshu1   

  1. 1.College of Fashion and Design, Donghua University, Shanghai 200051, China
    2. Key Laboratory of Clothing Design and Technology, Ministry of Education, Donghua University, Shanghai 200051, China
    3. Zhejiang Semir Garment Co., Ltd., Wenzhou, Zhejiang 362000, China
  • Received:2020-08-03 Revised:2020-02-03 Online:2021-05-15 Published:2021-05-20

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Abstract:

In order to regulate the intelligent manufacturing for factories making different types of clothing, 5 first-level indicators, 12 second-level indicators and 35 third-level evaluation indexing elements were used to construct the maturity evaluation model for intelligent manufacturing capacity, based on the multi-dimensional Analytic Network Process (ANP). Expert questionnaire was used to determine the weight relationship of the evaluation model indicators, and the ANP evaluation indicator modeling was carried out with the help of the Super Decision software. The newly constructed capability maturity evaluation model and the general model were compared and verified on the maturity of intelligent construction capabilities of different types of clothing enterprises. The results show that the newly constructed evaluation model can fully reflect the current status of the development of intelligent manufacturing in the clothing industry and can accurately reflects the overall development level of the enterprise's intelligent manufacturing with the construction of individual indicators. It can also help the enterprise to develop the application technology.

Key words: clothing intelligent manufacturing, capability maturity, comprehensive evaluation model, analytic network process, clothing factory

CLC Number: 

  • TS941.79

Tab.1

Different types of clothing enterprises intelligent manufacturing capability index"

各级指标组成 企业类型
一级环节要素 二级组成要素 三级功能要素 OEM ODM OBM
指标 评价值 指标 评价值 指标 评价值
设计 A 服装产品设计 A1 服装款式设计 A11 √ √
服装纸样CAD设计 A12 √ √
三维虚拟试衣 A13 √ √
设计数据库 A14 √ √
服装工艺设计 A2 工艺数据库 A21 √ √
生产仿真 A22 √ √
精益生产能力 A23 √ √
与其他系统集成 A3 CAD/PDM集成 A31 √ √
PLM/ERP集成 A32 √ √
生产 B 生产计划 B1 企业资源计划 B11 √ √ √
制造资源计划 B12 √ √ √
生产过程 B2 订单管理 B21 √ √ √
物料采购 B22 √ √ √
人员管理 B23 √ √ √
质量控制 B24 √ √ √
计划与调度 B25 √ √ √
生产作业 B26 √ √ √
生产可视化 B27 √ √ √
生产资源管理 B3 设备效率分析 B31 √ √ √
设备管理系统 B32 √ √ √
物流 C 智能仓储 C1 订单及库存控制 C11 √ √ √
货位管理 C13 √ √ √
入库与移库管理 C13 √ √ √
动态拣选与盘点 C14 √ √ √
智能物流 C2 设备控制系统 C21 √ √ √
路径控制系统 C22 √ √ √
仓储物流设备 C3 设施设备 C31 √ √ √
系统集成 C32 √ √ √
销售 D 供应链管控体系 D1 供应链管理 D11 √
企业信息门户 D2 供应商管理 D21 √
客户关系管理 D22 √
服务 E 客户服务 E1 客户个性化服务 E11 √
售后服务 E12 √
网络服务 E2 网络协同 E21 √
网络安全 E22 √

Fig.1

ANP evaluation model for the capability maturity of smart clothing factories"

Fig.2

Correlation network among indicators"

Tab.2

Comparison of index weights of production links in different types of enterprises"

层级 指标内容 指标权重
OEM ODM OBM
一级 生产 0.622 193 0.612 708 0.362 259
二级 生产计划 0.152 742 0.156 41 0.096 956
生产过程 0.457 896 0.423 315 0.265 251
生产资源管理 0.011 555 0.032 983 0.000 052
三级 企业资源计划 0.037 840 0.046 190 0.048 701
制造资源计划 0.114 902 0.110 220 0.048 255
订单管理 0.107 064 0.110 984 0.092 458
物料采购 0.105 089 0.096 848 0.064 034
人员管理 0.013 849 0.019 686 0.003 943
质量控制 0.008 755 0.005 977 0.005 051
计划与调度 0.082 306 0.072 297 0.048 017
生产作业 0.131 093 0.107 286 0.051 610
生产可视化 0.009 74 0.010 237 0.000 138
设备效率分析 0.009 238 0.017 226 0.000 017
设备管理系统 0.002 317 0.015 757 0.000 035

Fig.3

Comparison of analysis results of various enterprises' indicators"

Tab.3

Comparative analysis of evaluation results of different models"

服装企业 中国智能制造能力
成熟度评价模型		 服装企业能力
成熟度评价模型
综合得分 等级评定 综合得分 等级评定
SM 0.67 未达1级 1.89 第1级
(计划级)
PF 4.66 第4级
(优化级)		 9.12 第5级
(领先级)
BXN 3.68 第3级
(集成级)		 7.69 第4级
(优化级)
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